Princeton Visual AI Lab



  1. CornerNet-Lite: Efficient Keypoint Based Object Detection

    Hei Law, Yun Teng, Olga Russakovsky and Jia Deng.

    British Machine Vision Conference (BMVC), 2020.

    [paper] [bibtex] [code]
  2. Towards Unique and Informative Captioning of Images

    Zeyu Wang, Berthy Feng, Karthik Narasimhan and Olga Russakovsky.

    European Conference on Computer Vision (ECCV), 2020.

    [paper] [bibtex] [code] [1-min video] [10-min video]
  3. Human Uncertainty Makes Classification More Robust

    Joshua C. Peterson*, Ruairidh M. Battleday*, Thomas L. Griffiths and Olga Russakovsky. (* = equal contribution)

    International Conference on Computer Vision (ICCV), 2019.

    [paper] [bibtex]
  4. Predictive-Corrective Networks for Action Detection

    Achal Dave, Olga Russakovsky and Deva Ramanan.

    Computer Vision and Pattern Recognition (CVPR), 2017.

    [paper] [project] [bibtex]
  5. Learning to Learn from Noisy Web Videos

    Serena Yeung, Vignesh Ramanathan, Olga Russakovsky, Liyue Shen, Greg Mori and Li Fei-Fei.

    Computer Vision and Pattern Recognition (CVPR), 2017.

    [paper] [bibtex] [poster]
  6. Crowdsourcing in Computer Vision
    Adriana Kovashka, Olga Russakovsky, Li Fei-Fei and Kristen Grauman.

    Foundation and Trends in Computer Vision and Graphics, 2016.

    [paper] [bibtex]
  7. Towards More Gender Diversity in CS through an Artificial Intelligence Summer Program for High School Girls

    Marie E. Vachovsky, Grace Wu, Sorathan Chaturapruek, Olga Russakovsky, Rick Sommer, Li Fei-Fei.

    Special Interest Group on Computer Science Education (SIGCSE), 2016.

    [paper] [SAILORS camp homepage] [bibtex] [Wired article]
  8. Scaling up Object Detection

    Olga Russakovsky.

    PhD Thesis, Stanford University, 2015.

    [paper] [bibtex] [poster]
  9. Scalable Multi-Label Annotation

    Jia Deng, Olga Russakovsky, Jonathan Krause, Michael Bernstein, Alexander Berg and Li Fei-Fei.

    ACM Conference on Human Factors in Computing Systems (CHI), 2014.

    [paper] [bibtex] [slides]
  10. Attribute learning in large-scale datasets

    Olga Russakovsky and Li Fei-Fei.

    Parts and Attributes Workshop at European Conference on Computer Vision (ECCVW), 2010.

    [pdf] [bibtex] [slides odpslides pdf] [data]
  11. A Steiner tree approach to efficient object detection.

    Olga Russakovsky and Andrew Y. Ng.

    Computer Vision and Pattern Recognition (CVPR), 2010.

    [paper] [bibtex] [poster] [data]
  12. Autonomous operation of novel elevators for robot navigation

    Ellen Klingbeil, Blake Carpenter, Olga Russakovsky, Andrew Y. Ng.

    International Conference on Robotics and Automation (ICRA), 2010.

    [paper] [bibtex]
  13. Training Conditional Random Fields for maximum labelwise accuracy

    Samuel S. Gross, Olga Russakovsky, Chuong B. Do and Serafim Batzoglou.

    Advances in Neural Information Processing Systems (NeurIPS), 2007.

    [paper] [bibtex]

Acknowledgements:
We are grateful to the National Science Foundation, KAUST, Samsung, Princeton CSML DataX and Princeton SEAS Project X for their generous support of our research.